What is a neural network (simplified) in AI for Everyone - Interactive Quiz & Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a simple neural network layer using Python.

AI for Everyone

layer_output = input_data [1] weights + bias

Drag options to blanks, or click blank then click option'

A*

B/

C-

D+

Attempts:

3 left

💡 Hint

Common Mistakes

Using + instead of * causes wrong calculations.

The neural network layer multiplies input data by weights before adding bias.

2fill in blank

medium

Complete the code to apply an activation function to the neural network output.

AI for Everyone

activated_output = [1](layer_output)

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Amax

Brelu

Csum

Dmin

Attempts:

3 left

💡 Hint

Common Mistakes

Using sum or max does not apply activation correctly.

The ReLU function is a common activation that keeps positive values and sets negatives to zero.

3fill in blank

hard

Fix the error in the code to calculate the prediction from inputs and weights.

AI for Everyone

prediction = [1](inputs, weights)

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Adot

Bsubtract

Cdivide

Dadd

Attempts:

3 left

💡 Hint

Common Mistakes

Using add or subtract does not combine inputs and weights correctly.

The dot product multiplies inputs and weights element-wise and sums them, which is needed for prediction.

4fill in blank

hard

Fill both blanks to create a dictionary of squared inputs greater than 5.

AI for Everyone

result = {x: x[1]2 for x in inputs if x [2] 5}

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A**

B>

C<

D+

Attempts:

3 left

💡 Hint

Common Mistakes

Using '+' instead of '**' or '<' instead of '>' causes wrong results.

We square each input with '**2' and filter those greater than 5 with '>'.

5fill in blank

hard

Fill all three blanks to create a filtered dictionary with uppercase keys and values greater than 10.

AI for Everyone

filtered = [1]: [2] for [3], [2] in data.items() if [2] > 10

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Ak.upper()

Bv

Ck

Ditem

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'item' instead of 'k' or not converting keys to uppercase.

Keys are converted to uppercase with k.upper(), values are v, and iteration uses k for keys.